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Top 10 algorithms in data mining

✍ Scribed by Xindong Wu; Vipin Kumar; J. Ross Quinlan; Joydeep Ghosh; Qiang Yang; Hiroshi Motoda; Geoffrey J. McLachlan; Angus Ng; Bing Liu; Philip S. Yu; Zhi-Hua Zhou; Michael Steinbach; David J. Hand; Dan Steinberg

Book ID: 106280361
Publisher: Springer-Verlag
Year: 2007
Tongue: English
Weight: 783 KB
Volume: 14
Category: Article
ISSN: 0219-1377
DOI: 10.1007/s10115-007-0114-2

No coin nor oath required. For personal study only.

✦ Synopsis

This paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) in December 2006: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. These top 10 algorithms are among the most influential data mining algorithms in the research community. With each algorithm, we provide a description of the algorithm, discuss the impact of the algorithm, and review current and further research on the algorithm. These 10 algorithms cover classification,

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